Управление Docker контейнерами с помощью docker-py
docker-py – это официальная библиотека Python для Docker, предоставляющая API для взаимодействия с Docker Daemon. С её помощью можно автоматизировать процессы создания, запуска, остановки и удаления контейнеров, работы с образами, сетями и томами Docker.
import docker
# Создание клиента
client = docker.from_env()
# Запуск контейнера
container = client.containers.run("ubuntu:latest", "echo Hello, docker-py!", detach=True)
# Получение логов контейнера
print(container.logs().decode())
# Остановка и удаление контейнера
container.stop()
container.remove()
В данном примере мы создаем клиента Docker, используя переменные окружения текущей сессии. Затем мы запускаем контейнер из образа ubuntu:latest, выполняем в нем команду echo, выводим логи работы контейнера и в конце останавливаем и удаляем контейнер.
Управление образами с помощью docker-py:
# Получение списка всех образов
images = client.images.list()
# Вывод информации о каждом образе
for image in images:
print(f'ID: {image.id}, Теги: {image.tags}')
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#python#docker#dockerpy
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Dolphin is a smart AI tool that can analyze and understand complex document images, like pages with text, tables, formulas, and pictures. It works in two steps: first, it figures out the layout and reading order of the page; then, it quickly parses each element using special prompts. This makes it fast and accurate for turning document images into structured data like JSON or Markdown. You can use pre-trained models and easy code to process single pages, PDFs, or specific elements. This helps you save time and effort when extracting information from complicated documents efficiently.
https://github.com/bytedance/Dolphin
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GOODBYEADS offers powerful, regularly updated rules (over 215,000 ad blocks, 102,000 DNS blocks) in formats like AdGuard, Quantumult X, and SmartDNS, with GitHub and fast domestic links. It blocks ads, trackers, and malware from top sources for clean browsing. You gain faster page loads, better privacy, less data use, and fewer distractions on any device.
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Dashy is a free, open-source dashboard that lets you organize and access all your self-hosted services, apps, and web links from one central place, making it easy to manage and monitor everything you use regularly[1][2][4]. It comes with over 50 pre-built widgets for things like system monitoring, news, weather, and productivity, and you can customize the look and layout with themes, icons, and different views[4][5]. The main benefit is that Dashy saves you time and hassle by giving you a single, user-friendly page to launch and check on all your important services, with features like instant search, status indicators, and multi-language support[4][5].
https://github.com/Lissy93/dashy
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You can get daily emails recommending new arXiv research papers that match your interests by linking your Zotero library with the Zotero-arXiv-Daily tool. It automatically finds relevant papers based on what you have saved in Zotero, summarizes them with AI-generated short descriptions, and sends you links to PDFs and code if available. This service is free, easy to set up on GitHub with minimal configuration, and runs automatically every day, saving you time and effort in keeping up with new scientific papers tailored to your research areas. It helps you stay updated without manually searching arXiv[1].
https://github.com/TideDra/zotero-arxiv-daily
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Ragbits is a tool that helps build and deploy GenAI applications quickly. It offers features like swapping between many language models, ensuring safe interactions with these models, and connecting to various data storage systems. Ragbits also includes tools for managing data and testing prompts, making it easier to develop reliable AI applications. This helps users create more accurate and efficient AI systems by integrating the latest data and reducing errors. Overall, Ragbits makes it faster and more efficient to develop and deploy AI applications.
https://github.com/deepsense-ai/ragbits
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https://github.com/awslabs/mcp
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https://github.com/HKUDS/DeepTutor
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https://github.com/offa/android-foss